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Quantitative Developer | Trading Team

Jump TradingShanghai, China · Posted Aug 23, 2024
Full-time
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Description

Jump Trading established its dedication to the China market with the launch of our Shanghai office in late 2017 with the ambition of building an independently operational office. Due to this ambition, we are growing our competencies in Trading, Technology and Operations. We bring together the best of two worlds; A start-up environment powered by Global Jump Trading dedication and resources.

This position is part of software development in a trading team. As a Quantitative Developer, you will work on a core team of technologists that build and improve the platforms that drive the trading team. You will work closely with the quantitative researchers on the team to create and improve research, trading infrastructure, improve the scalability of the production systems, maintaining the production trading environment, troubleshooting problems, and developing software to automate and improve deployment, configuration, validation.

The team is looking for someone who will be passionate about development and demonstrates intellectual curiosity and an ability to solve difficult technical problems in a fast-paced and energetic environment.


What You'll Do:

  • Full cycle development including researching and prod system, writing, testing & debugging code, deployment of finished code into the production environment and ensuring that all code is checked into the source code control system.
  • Direct support of end users, trouble-shooting problems and upgrading applications
  • Monitoring, troubleshooting, break/fix of production trading system
  • Other duties as assigned or needed

Skills You’ll Need:

  • Efficient in python, C++ and able to develop/maintain code for prod applications
  • Strong analytical and problem solving skills
  • Must be extremely detail-oriented
  • Proven success working with large data sets
  • Self-directed and comfortable taking ownership of projects and responsibilities.
  • Reliable and predictable availability

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